Contact center systems routinely route customer contacts based on pre-existing knowledge of customer attributes such as business value, previous contacts, age, sex, location, etc. Much-less common are systems that route contacts based on more-dynamic attributes of the customer, such as the party's emotional state or state-of-mind. Yet, such systems provide a significant advantage for determining how and when to route a contact, what type of agent should handle the contact, or what should be attempted or avoided when the contact has been routed and the interaction begins. Examples of when knowing the customer's emotional state is advantageous include when deciding whether the contact-center agent should attempt to close a sale, attempt to cross-sell or upsell, or wait for another time when the customer might be in a more-receptive emotional state.
There is a considerable amount of prior art in the area of emotion-detection technology. Emotion detection uses audible, visual, and/or tactile measures to determine the emotion of a person—either the customer, the agent, or anyone else—that participates in a communication. The most common technique of emotion detection is to monitor the volume and pitch of speech of a person involved in a phone call.
Call-center prior-art that uses emotion detection includes monitoring of customer-agent interaction and using emotion detection to determine what action to take. Examples of actions include recording the interaction for later analysis, bridging a supervisor onto the call, placing an outbound conciliatory call from a supervisor to the customer, and providing different treatment to the customer the next time that the customer communicates with the contact-center. One such system is the Perform™ interactive-capture system from NICE Systems, which detects emotion during an interaction between a customer and an agent, detects problem calls by monitoring the caller's tone, pitch, and tempo, and notifies supervisors of problem calls, who may then decide to join the call or give the customer a call-back. Another such system is the Customer Data Controlled Routing from Avaya Inc., which uses emotion-detection capabilities during the flow of a call to decide whether or not to give alternative call treatment to the customer's next call. Other art of interest in this context includes the following.
U.S. Pat. No. 5,684,872 of Flockhart et al., titled “Prediction of a Caller's Motivation as a Basis for Selecting Treatment of an Incoming Call,” uses historical information, such as the number of times that a customer has called in the last 24 hours, or real-time information, such as that the customer is calling from a geographical area that is experiencing a problem, to determine the motivation of a caller, and then uses the determined motivation to select the treatment that it provides to the caller. No emotion detection is used.
U.S. Pat. No. 6,064,731 of Flockhart et al., titled “Arrangement for Improving Retention of a Call Center's Customers,” uses historical information, such as the number of times that a customer has abandoned from hold, the number of times that the customer has been transferred by an agent, whether the customer experienced excessively-long wait times, etc., to determine if the business relationship with this customer is at risk. This information is used to provide alternative treatment and routing to future calls of the customer. No emotion detection is used. No real-time information is used from the segmentation or queuing stages of the call to determine call treatment, routing, matching, or scripting.
U.S. Pat. No. 6,757,362 of Cooper et al., titled “Personal Virtual Assistant,” is not in the area of contact center technology, but it describes a computer-based personal assistant that monitors the emotional state of a user, and then adapts its speed, verboseness, and terminology based on this information about the user. This patent also does not cover determining the emotional state of a user during call segmentation and queuing, nor does it change the way that a customer contact is routed, matched to a specific agent, or handled by an agent script.
U.S. patent application Ser. No. 11/525,452 of Coughlan, filed on Sep. 22, 2006, and titled “Method and Apparatus for Measurement of Alertness of Call Center Agents,” uses auditory and visual monitoring to measure alertness of agents in a call center during customer-agent interactions. In cases where lack of alertness is detected, agents may be given unscheduled breaks. The emotional state of customers is not determined, nor is the routing or treatment of customer contacts changed based on emotional state.
U.S. Pat. No. 7,120,880 of Dryer et al., titled “Method and System for Real-Time Determination of a Subject's Interest Level to Media Content,” detects what visual information a subject is attentive to via gaze detection and tracking, and detects the level of interest by measuring gaze duration and level of arousal. Arousal level is determined via head and facial gesture detection and analysis and voice content and prosody detection and analysis.
U.S. Pat. No. 7,013,005 of Yacoub et al., titled “System and Method for Prioritizing Contacts” detects a caller's emotional state and generates a priority score. The priority score is used in conjunction with other criteria to prioritize a call in a call queue.
U.S. patent application publication 2007/0003032 Batini et al., titled “Selection of Incoming Call Screening Treatment Based on Emotional State Criterion” allows a caller to enter their emotional state at an Interactive Voice Response (IVR) system. The call is then screened using the entered emotional state.
The problem with existing systems is that they only detect an emotional state of the caller in a communication at one point in the communication or that they analyze the emotional state after completion of the communication. During a communication, the emotional state of the caller can change over time. As the communication is transferred between queues, IVR Systems, and different agents, a change in the emotional state of the caller is not monitored between the various stages/steps of the communication. As a result, existing systems fail to detect the change in emotion of the caller as the communication progresses through a contact center. This sometimes results in poor decisions by the contact center in determining on how to process/route the communication in the call center.